A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Открываем терминал и вводим команду: ssh-keygen -t rsa

-t - это ключ установки типа ключа
rsa - это тип ключа shh, ешё он может быть например ed25519
Возможные типы ssh ключей можно посмотреть командой в терминале:

• Problem: Players dump Charisma to boost Strength
• Mitigation: Charisma affects more mechanics (leadership, NPC reactions)
• Result: Still possible, but trade-offs are meaningful

• Approach: Complex stat scaling system
• Design: Each weapon scales with different stats

Runnable Implementation: https://github.com/hanyuancheung/llm-skill

This is a first-person record of how I took Karpathy's LLM-Wiki intuition and turned it, step by step, into the llm-skill project. I'll walk through: where I started, why I chose this particular layering, what each layer solves.

LUKS2 encrypted BTRFS system partition with Limine/Snapper integration and hybernate to swapfile

• Table of Contents
• Introduction
• Preparation
• Ensure proper network connectivity